Identifying Exceptional Talent in Science, Technology, Engineering, and Mathematics: Increasing Diversity and Assessing Creative Problem-Solving
Name:
Maker Identifying Exceptional ...
Size:
490.6Kb
Format:
PDF
Description:
Final Accepted Manuscript
Author
Maker, C. JuneAffiliation
Univ ArizonaIssue Date
2020-06-04Keywords
creative problem-solvingperformance-based assessments
concept maps
STEM
identification of exceptional talent
Metadata
Show full item recordPublisher
SAGE PublicationsCitation
Maker, C. J. (2020). Identifying Exceptional Talent in Science, Technology, Engineering, and Mathematics: Increasing Diversity and Assessing Creative Problem-Solving. Journal of Advanced Academics, 31(3), 161–210. https://doi.org/10.1177/1932202X20918203Journal
JOURNAL OF ADVANCED ACADEMICSRights
Copyright © The Author(s) 2020.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
In the Cultivating Diverse Talent in STEM project, funded by the National Science Foundation in the United States, new assessments were developed, field tested, used to identify students with exceptional talent in science, technology, engineering, and mathematics (STEM), and compared with existing methods (grade point average [GPA], letters of recommendation, self-statements). Students identified by both methods participated in an internship program in laboratories of scientists on the campus of an R1 university in the Southwest. Existing methods limited the diversity of students identified. Significant differences were found between students identified by the new methods (M2) and existing methods (M1) in GPA, ethnicity, and parent level of education. Ethnicity differences may be due to the ethnic makeup of the partner schools, but differences in GPA and parent level of education cannot be attributed to the location of schools. Although GPAs of M1 students were significantly higher (3.71) than those of M2 students (3.07) and M1 students came from higher income groups and schools in higher income areas, the M2 students scored higher on all the performance assessments of creative problem-solving and at similar levels on concept maps and mathematical problem-solving. Studies of the usefulness and psychometric properties of the new assessments are needed with different groups and in different contexts.ISSN
1932-202XEISSN
2162-9536Version
Final accepted manuscriptSponsors
National Science Foundationae974a485f413a2113503eed53cd6c53
10.1177/1932202x20918203